K-8 Lesson Plans on the Web
Carol Hurst's Children's Literature Site: K-2 Data Gathering and Analyzing
A sample chapter from Picturing Math by Carol Otis Hurst and Rebecca Otis (SRA/McGraw-Hill, 1996. ISBN 0-02-687367-2). "When we look up information to answer a question or to formulate new questions, we are gathering and analyzing data. When we conduct surveys and draw conclusions from them, we are gathering and analyzing data..." Includes a list of references: Picture Books for Data Gathering and Analyzing.
The Cereal Box Problem - A Lesson in Expected Value - George Reese
FREE INSIDE! Collect all six!! How many cereal boxes would you expect to buy to get all the prizes? - includes an online simulation.
A page by Ken White that allows students to gather data on virtual coin-flipping experiments. It includes access to past data and an article about coin-flipping.
Descriptive Statistics - Introduction (Central Tendency, Variation) - Jay Hill
This branch of statistics lays the foundation for all statistical knowledge, but it is not something that you should learn simply so you can use it in the distant future. Descriptive statistics can be used NOW, in English class, in physics class, in history, at the football stadium, in the grocery store.
Exponential Fit: Running to Conclusions - Ed Malczewski
This lesson explores the process of finding the best fitting exponential curve to sets of data. It requires Internet access, a bag of Skittles, and Microsoft Excel.
Graphs and Stories - Malcolm Swan, The Language of Graphs
"Most students leave school knowing how to plot a graph from a table of numerical values, but far fewer are competent at interpreting graphs. But in the real world interpretation is more important than plotting. This WWW page is about graph interpretation - the skill of putting a story to a graph. "
Hare and Tortoise Game - Chris Povich
Each turn consists of three moves. The player rolls a die a total of three
times per turn; after each roll, the player's marker is moved one place to the
left if the number on the die is odd and one place to the right if it is even. Students calculate probabilities of landing on different positions, and use Resampling Stats software to write a program that will model the hare/tortoise
The Hermit's Epidemic - Jay Hill
Expected value has very practical applications. Despite the somewhat unrealistic nature of the Hermit Problem, it can show how expected value can be used in the study of infectious diseases. This project tracks the spread of a disease on a desert island with hermits on it. It uses the internet, a computer program (written in Future Basic), and other student activities to explore the concept of expected value (i.e. How many hermits do we expect to get the disease?).
Houston Area Real-Time Traffic Report - Susan Boone
Students calculated the time needed to travel a distance given the rate of speed; data were collected using "real-time" traffic maps of the greater Houston area and over a period of one week, one month, and one school year, traffic patterns were studied at various times of the day. At the completion of
the study students wrote a report and sent their results via email.
INDY 500 - Susan Boone
Students research information via the Internet to find the mean and median speed for the Indianapolis 500. Rates per lap are calculated, as well as the length of each lap.
Linear Regression - Amar Patel
Crickets move their wings faster in warm temperatures than in cold temperatures. Therefore, by listening to the pitch of their chirps, it is possible to tell the temperature of the air. A table gives the recorded pitch (in vibrations per second) of a cricket chirping recorded at 15 different temperatures - what if someone asked you what the temperature was, but you couldn't use a thermometer? Could you use the crickets? This lesson explores notions of relations between two variables, with many problems and activities to aid learning and classroom discussion.
"M&M's" - Introduction to
Probability - Chris Povich
"M&M's" Plain Chocolate Candies come in six colors: blue, brown, green,
orange, red, and yellow. Predict which color of "M&M's" will occur most in
the bag. Why did you predict these colors? A lesson that
addresses probability through M&M's and the graphing calculator.
For M&M data, see the History from "M&M's" Studios.
Min-Max Temperatures - John Meseke
Students use the predicted minimum and maximum temperatures for various cities throughout the U.S. to calculate averages.
NCAA Basketball Finals - John Meseke
A statistics lesson using data from the NCAA basketball finals. Looking at graphs from The Journal of Statistics Education, students discover reasons why teams from the 1950's and up have higher scores than teams from the 1940's.
Pop Clock - Susan Boone
Data collection, problem solving, research skills, and interpolation of data. Students review the Census Bureau's home page on the Internet and gather data regarding trends in population. They study these data and make predictions on future populations, comparing their results with the information available on the Internet.
The Probable Pen in the Cereal Box - Michael Cornell
How many boxes of cereal do you have to buy until you have received six pens of different colors? A cooperative classroom project during which participants calculated the expected value of a simple probability problem via experimentation.
Standard Deviation, Part 1 - Barbara Christopher
Students use the Internet to find statistical data for investigations that use the mean, standard deviation, and percentage error; calculate the standard deviation of monthly temperature means; and draw conclusions from the standard deviations and percentage error of these means.
Standard Deviation, Part 2 - Barbara Christopher
A followup to Standard Deviation, Part 1. Students use the Internet to gather temperature data from 3 cities; calculate the standard deviation and percentage error of the gathered temperatures; and prove or disprove a hypothesis on the basis of these statistics.
Weather Plots - John Meseke
Looking at graphs of temperature and humidity, students determine that the two graphs are inversely proportional. The data set consists of two curves of the flow of the temperature and the percent humidity for seven days at Boulder,
Colorado. It can be used by having students look at the relation between temperature and humidity, studying the two curves, and formulating a relation between them.